{"id":1425,"date":"2026-05-24T15:29:31","date_gmt":"2026-05-24T15:29:31","guid":{"rendered":"https:\/\/lean-app.com\/?p=1425"},"modified":"2026-09-08T18:18:27","modified_gmt":"2026-09-08T18:18:27","slug":"lean-vs-noom","status":"publish","type":"post","link":"https:\/\/lean-app.com\/es\/lean-vs-noom\/","title":{"rendered":"Lean frente a Noom: coaching psicol\u00f3gico frente a la precisi\u00f3n metab\u00f3lica"},"content":{"rendered":"<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp\" 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18px;border-radius:14px;color:#fff;font-family:var(--font-display);font-weight:500;font-size:15px;letter-spacing:-.01em;display:flex;justify-content:space-between;align-items:center;box-shadow:0 6px 18px rgba(0,0,0,.06)}\n#lvm-shell .pyramid .level .k{font-family:var(--font-mono);font-size:10px;text-transform:uppercase;letter-spacing:.08em;opacity:.75}\n#lvm-shell .pyramid .l1{background:#0E0E10;width:100%}\n#lvm-shell .pyramid .l2{background:#1D1D1F;width:84%}\n#lvm-shell .pyramid .l3{background:#3a3a3c;width:68%}\n#lvm-shell .pyramid .l4{background:var(--pink);width:52%}\n#lvm-shell .pyramid-cap{text-align:center;font-size:13px;color:var(--muted);margin-top:14px}\n\n\/* Section 7 honnetete : scorecard horizontal bars *\/\n#lvm-shell .scorecard{margin:30px 0 10px;border:1px solid var(--rule);border-radius:20px;padding:28px 26px;background:#fff}\n#lvm-shell .scorecard-head{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding-bottom:18px;margin-bottom:8px;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-head .h-crit{font-family:var(--font-mono);font-size:11px;font-weight:500;text-transform:uppercase;letter-spacing:.08em;color:var(--muted)}\n#lvm-shell .scorecard-head .h-brand{display:flex;align-items:center;gap:8px;font-family:var(--font-display);font-size:14px;font-weight:600;color:var(--ink)}\n#lvm-shell .scorecard-head .h-brand img{width:22px;height:22px;border-radius:5px;object-fit:cover}\n#lvm-shell .scorecard-row{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding:14px 0;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-row:last-child{border-bottom:0}\n#lvm-shell .scorecard-row .crit{font-size:14px;color:var(--ink);font-weight:500;padding-right:14px}\n#lvm-shell .scorecard-row .bar{display:flex;flex-direction:row-reverse;align-items:center;gap:10px}\n#lvm-shell .scorecard-row .bar .b{flex:1;height:8px;border-radius:99px;background:var(--rule-soft);overflow:hidden;position:relative}\n#lvm-shell .scorecard-row .bar .b > i{display:block;height:100%;border-radius:99px;transition:width 1s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .scorecard-row .bar.lean .b > i{background:var(--pink)}\n#lvm-shell .scorecard-row .bar.mfp .b > i{background:var(--mfp)}\n#lvm-shell .scorecard-row .bar .v{font-family:var(--font-mono);font-size:12px;font-weight:600;color:var(--ink);min-width:32px;text-align:left}\n\n\/* Section 8 pour qui : persona checklist *\/\n#lvm-shell .persona{margin:28px 0 10px;display:grid;grid-template-columns:1fr;gap:14px}\n#lvm-shell .persona-it{display:grid;grid-template-columns:54px 1fr;gap:16px;padding:22px 24px;background:#fff;border:1px solid var(--rule);border-radius:18px;align-items:center}\n#lvm-shell .persona-it.match{background:var(--pink-soft);border-color:rgba(255,45,110,.25)}\n#lvm-shell .persona-it .pic{width:54px;height:54px;border-radius:50%;display:flex;align-items:center;justify-content:center;background:var(--rule-soft);position:relative;font-family:var(--font-mono);font-size:13px;font-weight:600;color:var(--ink)}\n#lvm-shell .persona-it.match .pic{background:var(--pink);color:#fff}\n#lvm-shell .persona-it .pic svg{width:24px;height:24px}\n#lvm-shell .persona-it h4{margin:0 0 4px;font-size:17px;letter-spacing:-.01em}\n#lvm-shell .persona-it p{margin:0;font-size:14px;color:var(--muted);line-height:1.55}\n#lvm-shell .persona-it.match h4{color:var(--ink)}\n\n\/* Section 9 migration : timeline steps *\/\n#lvm-shell .steps{display:grid;grid-template-columns:repeat(5,1fr);gap:14px;margin:28px 0;position:relative}\n#lvm-shell .steps::before{content:\"\";position:absolute;top:14px;left:7px;right:calc(20% - 18px);height:1px;background:linear-gradient(90deg,var(--pink) 0%,var(--rule-soft) 100%);z-index:0}\n#lvm-shell .step{position:relative;padding-top:24px;z-index:1}\n#lvm-shell .step::before{content:\"\";position:absolute;top:8px;left:0;width:14px;height:14px;border-radius:50%;background:var(--pink);border:3px solid #fff;box-shadow:0 0 0 1px var(--rule)}\n#lvm-shell .step .sn{font-family:var(--font-mono);font-size:11px;color:var(--pink);font-weight:600;letter-spacing:.08em}\n#lvm-shell .step h4{margin:6px 0 6px;font-size:15px;letter-spacing:-.01em}\n#lvm-shell .step p{font-size:13px;color:var(--muted);line-height:1.5;margin:0}\n\n\/* Section 10 debloque : feature stack numbered XL *\/\n#lvm-shell .feat-stack{margin:30px 0 10px;border-top:1px solid var(--rule)}\n#lvm-shell .feat-it{display:grid;grid-template-columns:auto 1fr auto;gap:24px;padding:26px 0;border-bottom:1px solid var(--rule);align-items:center}\n#lvm-shell .feat-it .fn{font-family:var(--font-display);font-size:48px;font-weight:600;color:var(--pink);line-height:1;letter-spacing:-.04em;width:74px}\n#lvm-shell .feat-it .ft{font-family:var(--font-display);font-size:22px;font-weight:600;color:var(--ink);letter-spacing:-.015em;line-height:1.25;margin-bottom:6px}\n#lvm-shell .feat-it .fd{font-size:15px;color:var(--muted);line-height:1.55;margin:0}\n#lvm-shell .feat-it .fc{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--muted);font-weight:500}\n#lvm-shell .feat-it:last-child{border-bottom:0}\n\n#lvm-shell .faq{margin:22px 0}\n#lvm-shell .faq details{border-bottom:1px solid var(--rule);padding:20px 0}\n#lvm-shell .faq details:first-of-type{border-top:1px solid var(--rule)}\n#lvm-shell .faq summary{cursor:pointer;list-style:none;display:flex;justify-content:space-between;align-items:center;gap:18px;font-family:var(--font-display);font-size:20px;font-weight:500;letter-spacing:-.015em;color:var(--ink)}\n#lvm-shell .faq summary::-webkit-details-marker{display:none}\n#lvm-shell .faq summary::after{content:\"+\";font-size:24px;color:var(--muted);font-weight:300;line-height:1;transition:transform .25s, color .25s}\n#lvm-shell .faq details[open] summary::after{transform:rotate(45deg);color:var(--pink)}\n#lvm-shell .faq details[open] summary{color:var(--pink)}\n#lvm-shell .faq .ans{margin-top:14px;font-size:16px;color:var(--muted);line-height:1.65}\n\n#lvm-shell .get-band{background:var(--paper-2);border-radius:24px;padding:48px 36px;margin:60px 0 40px;text-align:center}\n#lvm-shell .get-band .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;color:var(--pink);font-weight:600;letter-spacing:.1em;margin-bottom:14px}\n#lvm-shell .get-band h3{font-size:36px;margin:0 0 14px;letter-spacing:-.025em}\n#lvm-shell .get-band p{font-size:16px;color:var(--muted);max-width:480px;margin:0 auto 26px}\n#lvm-shell .get-band .stores{display:flex;justify-content:center;gap:14px;flex-wrap:wrap}\n#lvm-shell .get-band .stores a{line-height:0;transition:transform .15s}\n#lvm-shell .get-band .stores a:hover{transform:translateY(-3px)}\n#lvm-shell .get-band .stores img{height:60px;width:auto;border-radius:11px}\n\n#lvm-shell .sources{font-size:14px;color:var(--muted);line-height:1.7}\n#lvm-shell .sources ol{padding-left:22px}\n#lvm-shell .sources li{margin-bottom:8px}\n\n#lvm-shell footer{padding:50px 0 60px;border-top:1px solid var(--rule);margin-top:40px}\n#lvm-shell footer .row{display:flex;justify-content:space-between;align-items:center;gap:18px;flex-wrap:wrap}\n#lvm-shell footer .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--pink);font-weight:600}\n#lvm-shell footer p{font-size:13px;color:var(--muted);margin:8px 0 0}\n#lvm-shell footer .stores{display:flex;gap:8px}\n#lvm-shell footer .stores img{height:34px;width:auto;border-radius:6px}\n\n#lvm-shell .rev{opacity:0;transform:translateY(12px);transition:opacity .8s cubic-bezier(.22,.61,.36,1),transform .8s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .rev.on{opacity:1;transform:translateY(0)}\n@media (prefers-reduced-motion:reduce){#lvm-shell .rev{transition:none;opacity:1;transform:none}}\n\n@media (max-width:760px){\n  #lvm-shell .nav-row{padding:8px 18px;gap:8px}\n  #lvm-shell .nav-link{display:none}\n  #lvm-shell .nav-stores img{height:24px}\n  #lvm-shell .wrap{padding:0 22px}\n  #lvm-shell .hero{padding:34px 0 0}\n  #lvm-shell h1{font-size:46px;letter-spacing:-.035em}\n  #lvm-shell h1 .alt{font-size:.55em;margin-top:10px}\n  #lvm-shell .dek{font-size:20px}\n  #lvm-shell .hero-stores img{height:42px}\n  #lvm-shell .hero-bottom{grid-template-columns:1fr;gap:28px;margin:30px 0 40px;padding-top:24px;align-items:stretch}\n  #lvm-shell .phone-wrap{order:-1}\n  #lvm-shell .phone{width:240px}\n  #lvm-shell .tap-hint.desktop{display:none}\n  #lvm-shell .tap-hint.mobile{display:block;position:relative;left:auto;top:auto;text-align:center;margin:0 auto 10px;width:100%}\n  #lvm-shell .tap-hint.mobile .th-arrow{position:relative;display:block;margin:6px auto 0;width:34px;height:34px;transform:none;color:var(--pink)}\n  #lvm-shell .snippet{padding:24px 22px}\n  #lvm-shell .snippet p{font-size:18px}\n  #lvm-shell section{padding:48px 0}\n  #lvm-shell h2{font-size:34px;letter-spacing:-.03em}\n  #lvm-shell h3{font-size:24px}\n  #lvm-shell .section-label{margin-bottom:22px}\n  #lvm-shell .statement{padding:24px 0;margin:32px 0}\n  #lvm-shell .statement .num{font-size:44px}\n  #lvm-shell .statement .lbl{font-size:19px}\n  #lvm-shell .fig{padding:20px 14px 14px;border-radius:16px}\n  #lvm-shell .cv-wrap{height:310px}\n  #lvm-shell .method{grid-template-columns:1fr;gap:20px}\n  #lvm-shell .method.flip{grid-template-columns:1fr}\n  #lvm-shell .method.flip .m-phone{order:0}\n  #lvm-shell .mini-row{grid-template-columns:repeat(3,1fr);gap:10px}\n  #lvm-shell .mini-phone{padding:3px;border-radius:18px;border-width:1px;max-width:110px}\n  #lvm-shell .mini-phone .notch{width:42px;height:11px;border-radius:0 0 8px 8px}\n  #lvm-shell .mini-phone .scr{border-radius:15px}\n  #lvm-shell .mini-cap{font-size:10px}\n  #lvm-shell .mini-cap strong{font-size:13px}\n  #lvm-shell .duo-row{grid-template-columns:repeat(2,1fr);gap:12px}\n  #lvm-shell .duo-row .mini-phone{max-width:130px}\n  #lvm-shell .steps{grid-template-columns:1fr;gap:18px}\n  #lvm-shell .steps::before{display:none}\n  #lvm-shell .step{padding-top:0;padding-left:24px}\n  #lvm-shell .step::before{top:6px;left:0}\n  #lvm-shell .table-row{grid-template-columns:1.4fr .9fr .9fr}\n  #lvm-shell .table-row > .crit{padding:13px 12px;font-size:13px}\n  #lvm-shell .table-row > .cell{padding:13px 10px;font-size:12px;gap:8px}\n  #lvm-shell .table-row.head > div{padding:14px 12px;font-size:10px;gap:7px}\n  #lvm-shell .table-row.head .brand-cell img{width:20px;height:20px}\n  #lvm-shell .get-band{padding:36px 22px;border-radius:18px;margin:40px 0 30px}\n  #lvm-shell .get-band h3{font-size:28px}\n  #lvm-shell .get-band .stores img{height:50px}\n  #lvm-shell .cta-band{padding:22px;gap:14px}\n  #lvm-shell .cta-band .l{font-size:16px;min-width:0}\n  #lvm-shell .cta-band .stores img{height:38px}\n  #lvm-shell .faq summary{font-size:18px;gap:14px}\n  #lvm-shell .pyramid{max-width:100%}\n  #lvm-shell .pyramid .level{padding:11px 14px;font-size:14px}\n  #lvm-shell .scorecard{padding:20px 16px;border-radius:16px}\n  #lvm-shell .scorecard-head{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px}\n  #lvm-shell .scorecard-head .h-brand{font-size:12px;gap:5px}\n  #lvm-shell .scorecard-head .h-brand img{width:18px;height:18px}\n  #lvm-shell .scorecard-row{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px;padding:12px 0}\n  #lvm-shell .scorecard-row .crit{font-size:13px;padding-right:8px}\n  #lvm-shell .scorecard-row .bar{gap:6px}\n  #lvm-shell .scorecard-row .bar .v{font-size:11px;min-width:26px}\n  #lvm-shell .persona-it{grid-template-columns:44px 1fr;gap:12px;padding:16px 16px;border-radius:14px}\n  #lvm-shell .persona-it .pic{width:44px;height:44px;font-size:12px}\n  #lvm-shell .persona-it h4{font-size:15px}\n  #lvm-shell .persona-it p{font-size:13px}\n  #lvm-shell .feat-it{grid-template-columns:auto 1fr;gap:14px;padding:20px 0}\n  #lvm-shell .feat-it .fn{font-size:36px;width:54px}\n  #lvm-shell .feat-it .ft{font-size:18px}\n  #lvm-shell .feat-it .fd{font-size:13px}\n  #lvm-shell .feat-it .fc{display:none}\n}\n@media (max-width:480px){\n  #lvm-shell .phone-tabs{gap:5px}\n  #lvm-shell .phone-tabs button{padding:5px 8px;font-size:10px}\n  #lvm-shell .nav-stores{gap:4px}\n  #lvm-shell .nav-stores img{height:22px}\n  #lvm-shell .hero-stores img{height:40px}\n  #lvm-shell .crumb{font-size:12px}\n  #lvm-shell .table-row{grid-template-columns:1.3fr .85fr .85fr}\n  #lvm-shell .table-row > .crit{padding:11px 9px;font-size:12px}\n  #lvm-shell .table-row > .cell{padding:11px 8px;font-size:11px;gap:6px}\n  #lvm-shell .table-row.head > div{padding:11px 9px;font-size:9px;gap:5px}\n}<\/style>\n\n<style id=\"lvm-collision-reset\">\n\/* Hard reset for global theme styles that collide with our content *\/\nbody.postid-1425 #lvm-shell .hero{display:block!important;align-items:initial!important;justify-content:initial!important;text-align:left!important;flex-direction:initial!important;padding:54px 0 0!important}\nbody.postid-1425 #lvm-shell .wrap,\nbody.postid-1425 #lvm-shell main.wrap{display:block!important;max-width:760px!important;margin-left:auto!important;margin-right:auto!important;padding-left:28px!important;padding-right:28px!important}\n@media (max-width:820px){\n  body.postid-1425 #lvm-shell .wrap,\n  body.postid-1425 #lvm-shell main.wrap{padding-left:18px!important;padding-right:18px!important}\n}\nhtml, body{overflow-x:hidden!important}\nbody.postid-1425 #lvm-shell{overflow-x:hidden;max-width:100vw}\nbody.postid-1425 #lvm-shell *{max-width:100%}\nbody.postid-1425 #lvm-shell .nav-row{max-width:100vw;box-sizing:border-box}\nbody.postid-1425 #lvm-shell.force-show .rev{opacity:1!important;transform:none!important}\n\n\/* === A.1 PHONE BACKGROUND CLASSES === *\/\nbody.postid-1425 #lvm-shell .phone-bg{position:absolute;inset:0;width:100%;height:100%;background-size:cover;background-position:center top;background-repeat:no-repeat;transition:opacity .28s ease;background-color:#FAF0E6}\nbody.postid-1425 #lvm-shell .phone-bg.tab-depense{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.tab-bilan{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.tab-kcal{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.tab-strategie{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.sub-BMR{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.sub-NEAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.sub-EAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.sub-TEF{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp)}\n\n\/* === v11.3 CTA BANDS MOBILE (badges plus gros + centrage) === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .cta-band{flex-direction:column!important;align-items:center!important;text-align:center!important;padding:26px 22px!important;gap:20px!important}\n  body.postid-1425 #lvm-shell .cta-band .l{min-width:0!important;width:100%!important;font-size:16px!important;line-height:1.5!important;text-align:center!important}\n  body.postid-1425 #lvm-shell .cta-band .stores{width:100%!important;justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1425 #lvm-shell .cta-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1425 #lvm-shell .cta-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1425 #lvm-shell .cta-band .stores img{height:56px!important;width:100%!important;max-width:170px!important;object-fit:contain!important;object-position:center!important;border-radius:10px!important}\n  body.postid-1425 #lvm-shell .get-band{padding:38px 22px!important}\n  body.postid-1425 #lvm-shell .get-band .stores{justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1425 #lvm-shell .get-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1425 #lvm-shell .get-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1425 #lvm-shell .get-band .stores img{height:56px!important;width:100%!important;max-width:170px!important;object-fit:contain!important;object-position:center!important;border-radius:10px!important}\n  body.postid-1425 #lvm-shell .get-band h3{font-size:26px!important;line-height:1.2!important}\n  body.postid-1425 #lvm-shell .get-band p{font-size:15px!important}\n}\n\n\/* === v11.2 BRAND BANNER above table responsive === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .brand-banner img{width:54px!important;height:54px!important}\n  body.postid-1425 #lvm-shell .brand-banner > div{padding:16px 12px!important;gap:8px!important}\n  body.postid-1425 #lvm-shell .brand-banner > div > div{font-size:15px!important}\n}\n\n\/* === v11.4 SCORECARD partie 7: redesign mobile === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .scorecard{padding:18px 16px!important;border-radius:16px!important}\n  body.postid-1425 #lvm-shell .scorecard-head{display:none!important}\n  body.postid-1425 #lvm-shell .scorecard-row{\n    display:block!important;\n    padding:14px 0!important;\n    border-bottom:1px solid #E8E2D6!important;\n  }\n  body.postid-1425 #lvm-shell .scorecard-row .crit{\n    display:block!important;\n    font-size:13px!important;\n    font-weight:600!important;\n    color:#0E0E10!important;\n    margin-bottom:10px!important;\n    padding-right:0!important;\n  }\n  body.postid-1425 #lvm-shell .scorecard-row .bar{\n    display:grid!important;\n    grid-template-columns:54px 1fr 32px!important;\n    column-gap:8px!important;\n    align-items:center!important;\n    padding:5px 0!important;\n    flex-direction:initial!important;\n    position:relative!important;\n  }\n  body.postid-1425 #lvm-shell .scorecard-row .bar::before{\n    content:attr(data-brand)!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:11px!important;\n    font-weight:600!important;\n    text-transform:uppercase!important;\n    letter-spacing:.05em!important;\n    color:#0E0E10!important;\n  }\n  body.postid-1425 #lvm-shell .scorecard-row .bar.lean::before{color:#FF2D6E!important}\n  body.postid-1425 #lvm-shell .scorecard-row .bar.mfp::before{color:#5B7FFF!important}\n  body.postid-1425 #lvm-shell .scorecard-row .bar .b{\n    height:10px!important;\n    width:100%!important;\n    border-radius:99px!important;\n    position:relative!important;\n    background:#EFEAE0!important;\n    overflow:hidden!important;\n  }\n  body.postid-1425 #lvm-shell .scorecard-row .bar .b > i{\n    display:block!important;\n    height:100%!important;\n    border-radius:99px!important;\n  }\n  body.postid-1425 #lvm-shell .scorecard-row .bar .v{\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:12px!important;\n    font-weight:700!important;\n    color:#0E0E10!important;\n    min-width:0!important;\n    text-align:right!important;\n  }\n}\n\n\/* === A.2 CHARTS MOBILE === *\/\n@media (max-width:760px){\n  \/* v13: charts FULL WIDTH (less card padding) + plus hauts pour vraie respiration *\/\n  body.postid-1425 #lvm-shell .cv-wrap{height:380px!important;min-height:360px!important;max-height:420px!important;width:100%!important}\n  body.postid-1425 #lvm-shell .cv-wrap canvas{width:100%!important;height:100%!important;display:block!important}\n  body.postid-1425 #lvm-shell .fig{padding:16px 4px 14px!important;margin:24px -4px 14px!important;overflow:visible!important}\n  body.postid-1425 #lvm-shell .fig-head{padding:0 12px!important;flex-wrap:wrap!important;gap:6px!important;margin-bottom:10px!important}\n  body.postid-1425 #lvm-shell .fig-body{padding:0 2px!important}\n  body.postid-1425 #lvm-shell .fig-cap{padding:0 12px!important;font-size:13px!important;margin-top:10px!important}\n}\n@media (max-width:480px){\n  body.postid-1425 #lvm-shell .cv-wrap{height:360px!important;min-height:340px!important;max-height:380px!important}\n  body.postid-1425 #lvm-shell .fig{padding:14px 2px 12px!important;margin:20px -6px 12px!important;border-radius:14px!important}\n  body.postid-1425 #lvm-shell .fig-body{padding:0!important}\n}\n\n\/* === v11.2 TABLEAU MOBILE STACKED CARDS avec mini-tags Lean\/MFP === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .table{border-radius:14px!important}\n  body.postid-1425 #lvm-shell .table-row.head{display:none!important}\n  body.postid-1425 #lvm-shell .table-row{\n    display:grid!important;\n    grid-template-columns:1fr 1fr!important;\n    grid-template-areas:\"crit crit\" \"lean mfp\"!important;\n    gap:0!important;\n    min-height:0!important;\n  }\n  body.postid-1425 #lvm-shell .table-row > .crit{\n    grid-area:crit!important;background:#0E0E10!important;color:#fff!important;\n    padding:11px 14px!important;font-size:13px!important;font-weight:600!important;\n    letter-spacing:-0.1px!important;border-right:0!important;line-height:1.35!important;\n    font-family:-apple-system,BlinkMacSystemFont,'SF Pro Display',sans-serif!important;text-transform:none!important;\n  }\n  body.postid-1425 #lvm-shell .table-row > .cell.lean{\n    grid-area:lean!important;border-right:1px solid #E8E2D6!important;\n    position:relative!important;background:#FFF1F5!important;padding-top:30px!important;\n  }\n  body.postid-1425 #lvm-shell .table-row > .cell:not(.lean):not(.crit){\n    grid-area:mfp!important;background:#F5F5F7!important;padding-top:30px!important;\n    position:relative!important;\n  }\n  body.postid-1425 #lvm-shell .table-row > .cell.lean::before{\n    content:\"LEAN\"!important;position:absolute!important;top:8px!important;left:12px!important;\n    right:auto!important;bottom:auto!important;width:auto!important;height:auto!important;\n    background:transparent!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:10px!important;font-weight:700!important;letter-spacing:.07em!important;\n    color:#FF2D6E!important;\n  }\n  body.postid-1425 #lvm-shell .table-row > .cell:not(.lean):not(.crit)::before{\n    content:\"NOOM\"!important;position:absolute!important;top:8px!important;left:12px!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:10px!important;font-weight:700!important;letter-spacing:.07em!important;\n    color:#FF6E5E!important;\n  }\n  body.postid-1425 #lvm-shell .table-row > .cell{\n    padding:12px 12px!important;font-size:13px!important;line-height:1.4!important;\n    align-items:flex-start!important;gap:7px!important;\n  }\n  body.postid-1425 #lvm-shell .icn{flex-shrink:0!important;margin-top:1px!important}\n}\n\n\/* === A.5 MINI-LOGOS partie 7 (triplet NEAT\/EAT\/TEF) === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .mini-row{gap:6px!important;margin:24px 0!important;grid-template-columns:repeat(3,1fr)!important}\n  body.postid-1425 #lvm-shell .mini-phone{max-width:100px!important;padding:2px!important;border-radius:14px!important;border-width:1px!important}\n  body.postid-1425 #lvm-shell .mini-phone.tiny{max-width:96px!important;padding:2px!important;border-radius:13px!important}\n  body.postid-1425 #lvm-shell .mini-phone .notch{width:30px!important;height:8px!important;border-radius:0 0 5px 5px!important}\n  body.postid-1425 #lvm-shell .mini-phone .scr{border-radius:11px!important}\n  body.postid-1425 #lvm-shell .mini-cap{font-size:10px!important;margin-top:8px!important}\n  body.postid-1425 #lvm-shell .mini-cap strong{font-size:12px!important;margin-top:2px!important}\n}\n\n\/* === MOCKUP TAP HINT MOBILE === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .tap-hint.mobile{position:relative!important;width:100%!important;left:auto!important;top:auto!important;text-align:center!important;margin:0 auto 14px!important;display:block!important}\n  body.postid-1425 #lvm-shell .tap-hint.desktop{display:none!important}\n  body.postid-1425 #lvm-shell .tap-hint.hidden{display:none!important;height:0!important;margin:0!important;padding:0!important}\n}\n\n\/* === A.6 BODYSCAN ILLUST partie BMR (override mobile mini-phone) === *\/\nbody.postid-1425 #lvm-shell .bodyscan-illust{margin:40px auto 8px!important;display:flex!important;flex-direction:column!important;align-items:center!important;gap:14px!important;max-width:220px!important}\nbody.postid-1425 #lvm-shell .bodyscan-illust .mini-phone{max-width:200px!important;padding:3px!important;border-radius:22px!important;border-width:1px!important}\nbody.postid-1425 #lvm-shell .bodyscan-illust .mini-phone .notch{width:40px!important;height:11px!important;border-radius:0 0 7px 7px!important}\nbody.postid-1425 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:18px!important}\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .bodyscan-illust{max-width:180px!important}\n  body.postid-1425 #lvm-shell .bodyscan-illust .mini-phone{max-width:160px!important;padding:3px!important;border-radius:20px!important}\n  body.postid-1425 #lvm-shell .bodyscan-illust .mini-phone .notch{width:34px!important;height:9px!important;border-radius:0 0 6px 6px!important}\n  body.postid-1425 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:16px!important}\n}\n<\/style>\n\n\n<div id=\"lvm-shell\"><div class=\"progress\" aria-hidden=\"true\"><i id=\"progBar\"><\/i><\/div>\n\n<header class=\"nav\">\n  <div class=\"nav-row\">\n    <a class=\"nav-brand\" href=\"https:\/\/lean-app.com\/es\/\" aria-label=\"Inicio Lean\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/>\n      <span>Lean<\/span>\n    <\/a>\n    <span class=\"nav-spacer\"><\/span>\n    <a class=\"nav-link\" href=\"https:\/\/lean-app.com\/es\/tdee-calculator\/\">Calculadora TDEE<\/a>\n    <div class=\"nav-stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\" aria-label=\"Descargar en el App Store\">\n        <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n      <\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\" aria-label=\"Disponible en Google Play\">\n        <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/>\n      <\/a>\n    <\/div>\n  <\/div>\n<\/header>\n\n<main class=\"wrap\">\n\n<section class=\"hero\" aria-labelledby=\"title\">\n  <div class=\"crumb\"><a href=\"https:\/\/lean-app.com\/es\/\">Inicio<\/a> &nbsp;\/&nbsp; Lean vs Noom<\/div>\n  <div class=\"eyebrow\">Comparativa &middot; Nutrici\u00f3n &amp; TDEE<\/div>\n  <h1 id=\"title\">Lean frente a Noom.\n    <span class=\"alt\">Coaching psicol\u00f3gico frente a la precisi\u00f3n metab\u00f3lica.<\/span>\n  <\/h1>\n  <p class=\"dek\">Noom vende coaching conductual para cambiar tus h\u00e1bitos. Lean ve tu gasto real. Dos promesas que no juegan en el mismo terreno.<\/p>\n  <div class=\"byline\">\n    <img class=\"by-logo\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/>\n    <span><strong>El equipo Lean<\/strong> &middot; Lectura 12&nbsp;min &middot; Actualizado el 24 de mayo de 2026<\/span>\n  <\/div>\n  <div class=\"hero-stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T\u00e9l\u00e9charger sur l'App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Disponible sur Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <span class=\"or\">Descarga gratuita<\/span>\n  <\/div>\n\n  <div class=\"hero-bottom\">\n    <div class=\"hero-lead\">\n      Noom es conocido por su cuestionario de registro largo y personalizado, sus cursos diarios de psicolog\u00eda alimentaria, su clasificaci\u00f3n de alimentos verde\/amarillo\/rojo y el acceso a un coach humano. Una fuerza real para la adherencia y el trabajo sobre los h\u00e1bitos. Pero su f\u00f3rmula del TDEE sigue siendo Mifflin-St Jeor 1990, m\u00e1s un factor de actividad est\u00e1tico que marcas una sola vez en el cuestionario de registro. Sin grasa corporal real medida en la app, sin adaptaci\u00f3n metab\u00f3lica. En 3 meses de definici\u00f3n seria, la brecha se agranda.\n    <\/div>\n    <div class=\"phone-wrap rev\">\n      <div class=\"phone-stage\">\n        <div class=\"tap-hint mobile\" id=\"tapHintMobile\" aria-hidden=\"true\">\n          <span class=\"th-pill\"><small>Demostraci\u00f3n interactiva<\/small>Toca la pantalla para explorar la aplicaci\u00f3n<\/span>\n          <svg class=\"th-arrow\" viewbox=\"0 0 24 24\" fill=\"none\" aria-hidden=\"true\">\n            <path d=\"M12 4 L12 20 M5 13 L12 20 L19 13\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\n          <\/svg>\n        <\/div>\n        <div class=\"tap-hint desktop\" id=\"tapHintDesktop\" aria-hidden=\"true\">\n          <span class=\"th-pill\"><small>Demostraci\u00f3n interactiva<\/small>Toca la pantalla<br>para explorar la aplicaci\u00f3n<\/span>\n          <svg class=\"th-arrow\" viewbox=\"0 0 104 34\" fill=\"none\" aria-hidden=\"true\">\n            <path d=\"M4 9 C 34 1, 64 20, 94 27\" stroke=\"currentColor\" stroke-width=\"2.6\" fill=\"none\" stroke-linecap=\"round\"\/>\n            <path d=\"M86 20 L 94 27 L 84 30\" stroke=\"currentColor\" stroke-width=\"2.6\" fill=\"none\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\n          <\/svg>\n        <\/div>\n        <div class=\"phone\" id=\"phone\" role=\"img\" aria-label=\"Vista general de la aplicaci\u00f3n Lean con desglose del TDEE\">\n          <div class=\"notch\"><\/div>\n          <div class=\"phone-screen\">\n            <button class=\"phone-back\" id=\"phoneBack\" aria-label=\"Volver\">&#8249;<\/button>\n            <div id=\"phoneImg\" class=\"phone-bg tab-depense\" role=\"img\" aria-label=\"Vista Lean, pesta\u00f1a Gasto\"><\/div>\n            <div class=\"phone-zones\" id=\"phoneZones\">\n              <div class=\"z\" data-sub=\"BMR\"  style=\"top:11%;height:21%\" role=\"button\" tabindex=\"0\" aria-label=\"Detalle BMR\"><\/div>\n              <div class=\"z\" data-sub=\"NEAT\" style=\"top:33%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"Detalle NEAT\"><\/div>\n              <div class=\"z\" data-sub=\"EAT\"  style=\"top:50%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"Detalle EAT\"><\/div>\n              <div class=\"z\" data-sub=\"TEF\"  style=\"top:67%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"Detalle TEF\"><\/div>\n            <\/div>\n            <div class=\"phone-navbar\" id=\"phoneNav\" aria-hidden=\"false\">\n              <button data-tab=\"bilan\"     type=\"button\" aria-label=\"Pesta\u00f1a Balance\"><\/button>\n              <button data-tab=\"kcal\"      type=\"button\" aria-label=\"Pesta\u00f1a Calor\u00edas\"><\/button>\n              <button data-tab=\"depense\"   type=\"button\" aria-label=\"Pesta\u00f1a Gasto\"><\/button>\n              <button data-tab=\"strategie\" type=\"button\" aria-label=\"Pesta\u00f1a Estrategia\"><\/button>\n            <\/div>\n          <\/div>\n        <\/div>\n        <div class=\"phone-tabs\" role=\"tablist\" aria-label=\"Navegar por la aplicaci\u00f3n Lean\">\n          <button data-tab=\"bilan\"     type=\"button\">Balance<\/button>\n          <button data-tab=\"kcal\"      type=\"button\">Calor\u00edas<\/button>\n          <button data-tab=\"depense\"   type=\"button\" class=\"on\">Gasto<\/button>\n          <button data-tab=\"strategie\" type=\"button\">Estrategia<\/button>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"snippet rev\">\n    <div class=\"lbl\">Respuesta r\u00e1pida<\/div>\n    <p>Noom calcula tu TDEE con Mifflin-St Jeor 1990 (sin grasa corporal medida en la app) y un factor de actividad est\u00e1tico elegido en el momento del cuestionario de registro. La fuerza real de Noom est\u00e1 en otra parte: un cuestionario personalizado que crea un fuerte compromiso inicial, cursos diarios de psicolog\u00eda alimentaria, una clasificaci\u00f3n verde\/amarillo\/rojo de los alimentos y el acceso a un coach humano que trabaja la adherencia. Lean toma un partido diferente: recalcular cada componente del TDEE (<span data-term=\"BMR\">BMR<span class=\"tt\">Basal Metabolic Rate. Energ\u00eda gastada en reposo. En Lean, calculada sobre la masa magra real mediante BodyScan IA.<\/span><\/span> sobre grasa corporal real mediante un modelo propietario patentado, <span data-term=\"NEAT\">NEAT<span class=\"tt\">Non-Exercise Activity Thermogenesis. Gasto ligado a los pasos y a las actividades cotidianas fuera del deporte.<\/span><\/span> por pasos, <span data-term=\"EAT\">EAT<span class=\"tt\">Exercise Activity Thermogenesis. Gasto ligado a las sesiones de deporte, calculado mediante MET.<\/span><\/span> por MET, <span data-term=\"TEF\">TEF<span class=\"tt\">Thermic Effect of Food. Energ\u00eda gastada por la digesti\u00f3n. Depende de los macros ingeridos.<\/span><\/span> por macros) y modular el BMR con la adaptaci\u00f3n metab\u00f3lica de forma continua, sin coeficiente que elegir.<\/p>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"constat\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">00 &middot; La constataci\u00f3n<\/span><\/div>\n  <h2 id=\"constat\">Noom vende coaching, no tu adaptaci\u00f3n metab\u00f3lica<\/h2>\n  <p>Si lees esto, probablemente ya has instalado Noom. Hiciste el cuestionario de registro largo, esos 20 minutos de preguntas muy personales sobre tu historia con el peso, tus bloqueos, tus emociones, tus h\u00e1bitos. Te sentiste comprendido. Introdujiste tu peso, tu altura, tu edad, tu sexo, y elegiste tu nivel de actividad en una lista est\u00e1tica. La app te mostr\u00f3 un objetivo cal\u00f3rico, digamos 1&nbsp;500&nbsp;kcal para perder peso.<\/p>\n  <p>Seguiste los cursos diarios de 5 a 10 minutos sobre psicolog\u00eda alimentaria. Clasificaste tus comidas en verde, amarillo, rojo. Hablaste con tu coach humano los d\u00edas dif\u00edciles. Las primeras 6 semanas, funciona. Pierdes. Est\u00e1s contento. Luego, hacia la semana 8, la b\u00e1scula se congela. Aprietas las tuercas. Bajas a 1&nbsp;350&nbsp;kcal. Otra vez, nada se mueve.<\/p>\n\n  <div class=\"statement\">\n    <div class=\"num\">&minus;10 a &minus;15&nbsp;%<\/div>\n    <div class=\"lbl\">de bajada medida del TDEE tras 4 a 6 semanas de d\u00e9ficit a &minus;500&nbsp;kcal\/d\u00eda. Noom no lo detecta. Tu objetivo cal\u00f3rico se queda congelado en el factor de actividad que marcaste en el cuestionario de registro, hace 100&nbsp;d\u00edas.<\/div>\n  <\/div>\n\n  <p>Imaginemos que Noom te muestra un TDEE de 2&nbsp;000&nbsp;kcal. Comes 1&nbsp;500 (d\u00e9ficit te\u00f3rico de 500&nbsp;kcal). Pero en realidad, tu <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/depense-energetique-totale-v2\/\">TDEE ha bajado a 1&nbsp;700&nbsp;kcal<\/a> por la adaptaci\u00f3n metab\u00f3lica. Est\u00e1s a solo 200&nbsp;kcal de d\u00e9ficit real, no 500. La p\u00e9rdida se ralentiza dr\u00e1sticamente. Ning\u00fan curso diario de Noom puede corregir eso, porque el problema no est\u00e1 en tu cabeza, est\u00e1 en la ecuaci\u00f3n.<\/p>\n  <p>La promesa de Noom es clara y se cumple en su parte conductual: te sientes acompa\u00f1ado, trabajas tus desencadenantes emocionales, aprendes a clasificar la calidad de tus elecciones. Es valioso para la adherencia. Lo que Noom no hace es <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/comment-compter-ses-calories\/\">recalcular tu gasto<\/a> a lo largo de las semanas de d\u00e9ficit. Y es exactamente ah\u00ed donde la promesa \u00abcalorie tracker\u00bb se detiene, cuando es la palanca que hace perder peso.<\/p>\n<\/section>\n\n<section aria-labelledby=\"p1\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">01 &middot; Problema 1<\/span><\/div>\n  <h2 id=\"p1\">La f\u00f3rmula BMR de 1990, sin grasa corporal medida en la app<\/h2>\n  <p>Detr\u00e1s de los cursos diarios y la clasificaci\u00f3n de alimentos, Noom tiene que fijar una cifra: tu metabolismo basal, la energ\u00eda quemada en reposo. La obtiene con la ecuaci\u00f3n de Mifflin-St Jeor, la que usa la inmensa mayor\u00eda de los trackers de consumo.<\/p>\n  <p>Mifflin-St Jeor data de 1990. Sobre el papel es un progreso: 498 sujetos, calorimetr\u00eda indirecta, poblaci\u00f3n m\u00e1s representativa que los trabajos de 1919. Noom la aplica tal cual, sin variante.<\/p>\n  <p>Algunos competidores ofrecen al menos una salida, la ecuaci\u00f3n Katch-McArdle, que trabaja sobre la masa magra si introduces tu porcentaje de grasa. Noom no ofrece esa opci\u00f3n: sin campo de grasa corporal, sin c\u00e1lculo alternativo. El coaching se apoya por tanto en una estimaci\u00f3n que nada viene a corregir.<\/p>\n  <p>El progreso de 1990 sobre 1919 es real pero marginal, porque el defecto de fondo no se mueve: la ecuaci\u00f3n solo conoce tu peso. Ni tu grasa corporal, ni tu masa magra.<\/p>\n  <p>Y la masa grasa consume muy poca energ\u00eda en reposo. Son los \u00f3rganos y los m\u00fasculos los que gastan: el h\u00edgado, el cerebro, el coraz\u00f3n, los ri\u00f1ones. Dos cuerpos del mismo peso con composiciones diferentes no tienen por tanto el mismo metabolismo.<\/p>\n  <p>Frankenfield 2013 (PubMed 23631843) confront\u00f3 Mifflin-St Jeor con la calorimetr\u00eda indirecta de referencia: 87&nbsp;% de precisi\u00f3n en los sujetos no obesos, pero solo 68&nbsp;% en los sujetos obesos, con desviaciones que alcanzan 330&nbsp;kcal al d\u00eda.<\/p>\n\n  <p style=\"margin-bottom:8px\"><strong>Ejemplo con cifras.<\/strong> Mujer de 1,65 m, 85&nbsp;kg, 38&nbsp;% de grasa corporal:<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figura 1<\/span><span class=\"r\">kcal<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\"><canvas id=\"chartBMR\" aria-label=\"Comparaci\u00f3n BMR Mifflin-St Jeor 1670 kcal vs modelo propietario patentado Lean 1340 kcal, diferencia de 330 kcal\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>BMR estimado<\/strong> para una mujer de 1,65 m, 85&nbsp;kg, 38&nbsp;% de grasa corporal. El modelo propietario patentado Lean tiene en cuenta la masa magra. Mifflin-St Jeor (Noom por defecto, sin opci\u00f3n de masa magra), no. Diferencia de 330&nbsp;kcal, es decir, el equivalente a una comida ligera entera.<\/p>\n  <\/div>\n\n  <p>330&nbsp;kcal de error es la diferencia entre un d\u00e9ficit que funciona y una meseta inexplicada. Ning\u00fan acompa\u00f1amiento conductual, por bueno que sea, recupera un objetivo cal\u00f3rico falso desde el principio: simplemente te har\u00e1 m\u00e1s constante en la diana equivocada.<\/p>\n\n  <div class=\"bodyscan-illust\" style=\"margin:40px auto 8px;display:flex;flex-direction:column;align-items:center;gap:14px;max-width:200px\">\n    <div class=\"mini-phone\" style=\"max-width:200px\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-bodyscan-result.webp\" alt=\"BodyScan IA Lean : bodyfat mesur\u00e9 par photo en 5 secondes\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n    <div class=\"mini-cap\">Grasa corporal real<strong>Foto, 5 segundos<\/strong><\/div>\n  <\/div>\n\n  <div class=\"statement\">\n    <div class=\"num\">400&nbsp;kcal<\/div>\n    <div class=\"lbl\">de diferencia entre dos mujeres de 75&nbsp;kg, una al 22&nbsp;% de grasa corporal (BMR 1&nbsp;650), la otra al 38&nbsp;% (BMR 1&nbsp;250). Noom les da la misma cifra, sin opci\u00f3n de masa magra.<\/div>\n  <\/div>\n\n  <p>La conclusi\u00f3n es aritm\u00e9tica: una app que solo conoce tu peso, tu altura, tu edad y tu sexo no puede individualizar tu metabolismo. Le falta la variable que cuenta.<\/p>\n<\/section>\n\n<section aria-labelledby=\"p2\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">02 &middot; Problema 2<\/span><\/div>\n  <h2 id=\"p2\">El factor de actividad, elegido de una vez por todas<\/h2>\n  <p>Es el eslab\u00f3n que el coaching no puede compensar.<\/p>\n  <p>Una vez estimado el metabolismo basal, Noom tiene que deducir tu gasto total: el BMR m\u00e1s los pasos, las actividades cotidianas, las sesiones y la digesti\u00f3n.<\/p>\n  <p>El m\u00e9todo cabe en una pregunta del cuestionario de registro: elige tu nivel de actividad en una lista. Ese coeficiente se llama PAL, por Physical Activity Level.<\/p>\n  <ul>\n    <li>Sedentaria (PAL 1,25): oficina, poca caminata<\/li>\n    <li>Ligeramente activa (PAL 1,4): caminata ocasional, poco deporte<\/li>\n    <li>Activa (PAL 1,6): caminata regular, deporte 3 a 5 veces por semana<\/li>\n    <li>Muy activa (PAL 1,8): deporte intenso casi diario o trabajo f\u00edsico<\/li>\n  <\/ul>\n  <p>El BMR se multiplica despu\u00e9s por ese n\u00famero. Es todo el mecanismo detr\u00e1s de tu objetivo diario: una casilla marcada el primer d\u00eda, nunca vuelta a discutir.<\/p>\n  <p>La aproximaci\u00f3n es burda. Entre un domingo en el sof\u00e1 y un d\u00eda de pie caminando, la diferencia real supera con creces lo que un coeficiente \u00fanico puede representar.<\/p>\n  <p>Noom se sincroniza correctamente con Apple Health y Google Fit y recupera tus pasos. Un bonus cal\u00f3rico puede a\u00f1adirse cuando se detecta una sesi\u00f3n. Pero la base del c\u00e1lculo sigue siendo el multiplicador elegido en el registro.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figura 2 &middot; 7 d\u00edas reales<\/span><span class=\"r\">kcal\/d\u00eda<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\"><canvas id=\"chartNEAT\" aria-label=\"Variabilidad diaria del gasto cal\u00f3rico en 7 d\u00edas, frente a 2000 kcal fijas seg\u00fan Noom\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Gasto real<\/strong> medido durante 7&nbsp;d\u00edas en una usuaria de Lean. La l\u00ednea gris es lo que mostraba Noom (2&nbsp;000&nbsp;kcal fijas, PAL Activa \u00d7 BMR). Las anotaciones rosas muestran por qu\u00e9 cada d\u00eda se mueve.<\/p>\n  <\/div>\n\n  <p>Tu actividad no cabe en una casilla. Puedes ser muy activo la semana en que encadenas desplazamientos, y sedentario la que trabajas a distancia.<\/p>\n  <p>\u00bfQu\u00e9 casilla marcar, entonces? Ninguna es correcta, y el TDEE mostrado sigue desplazado de forma duradera respecto al real.<\/p>\n  <p>Es el punto central: incluso con una ecuaci\u00f3n de metabolismo moderna, un PAL est\u00e1tico basta para falsear el conjunto. El NEAT, el EAT y el TEF no se deducen de un multiplicador \u00fanico.<\/p>\n  <p>Un metabolismo estimado sin medici\u00f3n de la composici\u00f3n corporal, m\u00e1s un gasto de actividad aproximado por un coeficiente congelado: las posibilidades de que el objetivo final sea correcto son bajas.<\/p>\n\n  <div class=\"cta-band rev\">\n    <div class=\"l\">Ver tu TDEE real, desglosado en BMR + NEAT + EAT + TEF. Descarga gratuita.<\/div>\n    <div class=\"stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"p3\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">03 &middot; Problema 3<\/span><\/div>\n  <h2 id=\"p3\">La adaptaci\u00f3n metab\u00f3lica, nunca modelizada<\/h2>\n  <p>Es el punto ciego que ni los cursos diarios ni los coaches cubren.<\/p>\n  <p>En d\u00e9ficit prolongado, tu cuerpo constata que recibe menos energ\u00eda y reduce su consumo. Como un tel\u00e9fono que pasa a modo ahorro: todo sigue funcionando, pero a menor velocidad.<\/p>\n  <p>Es la adaptaci\u00f3n metab\u00f3lica, y la literatura es constante: M\u00fcller 2015 (PubMed 26399868, rean\u00e1lisis del estudio de Minnesota), Doucet 2001 sobre el d\u00e9ficit prolongado, Nunes 2020 (PMC7484122). Las horquillas publicadas van del 5 al 25&nbsp;% del metabolismo basal.<\/p>\n  <ul>\n    <li>D\u00e9ficit de &minus;250&nbsp;kcal al d\u00eda, durante 2 a 8 semanas: adaptaci\u00f3n del <strong>del 5 al 10&nbsp;%<\/strong> (el TDEE baja al 90-95&nbsp;% del nivel inicial)<\/li>\n    <li>D\u00e9ficit de &minus;500&nbsp;kcal al d\u00eda: <strong>10 a 15&nbsp;%<\/strong> de adaptaci\u00f3n (el TDEE baja al 85-90&nbsp;%)<\/li>\n    <li>D\u00e9ficit de &minus;750&nbsp;kcal al d\u00eda: <strong>15 a 25&nbsp;%<\/strong> de adaptaci\u00f3n (el TDEE baja al 75-85&nbsp;%)<\/li>\n  <\/ul>\n  <p>Convenci\u00f3n Lean: 100&nbsp;% significa un metabolismo \u00f3ptimo, 90&nbsp;% una adaptaci\u00f3n del 10&nbsp;%. Y como el NEAT, el EAT y el TEF se calculan todos a partir del BMR, es todo el TDEE el que se desplaza.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figura 3 &middot; 8 semanas en d\u00e9ficit<\/span><span class=\"r\">kcal\/d\u00eda<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\"><canvas id=\"chartAdapt\" aria-label=\"TDEE que cae de 2000 a 1720 kcal en 8 semanas, frente a 2000 fijas seg\u00fan Noom\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>TDEE real<\/strong> en 8 semanas de d\u00e9ficit a &minus;500&nbsp;kcal\/d\u00eda. La curva rosa baja. La l\u00ednea de Noom se queda plana. En la semana 6, ya est\u00e1s en mantenimiento. Sin haber cambiado nada.<\/p>\n  <\/div>\n\n  <p>Un ejemplo con cifras: buscas un d\u00e9ficit del 25&nbsp;% sobre un TDEE de 2&nbsp;000&nbsp;kcal, es decir, 1&nbsp;500&nbsp;kcal al d\u00eda. Tu cuerpo se adapta un 14&nbsp;%, tu TDEE real cae a 1&nbsp;720. Solo te quedan 220&nbsp;kcal de d\u00e9ficit: la p\u00e9rdida se detiene, sin que hayas cambiado nada.<\/p>\n  <p>Lo que hace temible el fen\u00f3meno es su lentitud. Las primeras semanas funcionan, tienes confianza, sigues. La adaptaci\u00f3n se acumula en silencio hasta el d\u00eda en que la b\u00e1scula se congela.<\/p>\n  <p>Es precisamente el momento en que un acompa\u00f1amiento conductual se vuelve contra ti. El coach te explicar\u00e1 que la meseta es normal, que hay que perseverar, revisar tus h\u00e1bitos. Cuando el problema no es ni tu disciplina ni tu motivaci\u00f3n: es la cifra objetivo la que se ha movido, y nadie la ha medido.<\/p>\n  <p>Noom no modeliza este fen\u00f3meno. Tu objetivo cal\u00f3rico se queda congelado mientras no actualices tu peso a mano. Puedes seguir todos los cursos y clasificar cada alimento: si la diana es falsa, el m\u00e9todo no puede rescatarte.<\/p>\n<\/section>\n\n<section aria-labelledby=\"solution\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">04 &middot; Soluci\u00f3n Lean<\/span><\/div>\n  <h2 id=\"solution\">C\u00f3mo Lean resuelve cada uno de los 3 problemas<\/h2>\n  <p>Noom y Lean no juegan en el mismo terreno. Noom apuesta por la psicolog\u00eda del comportamiento: cursos diarios, coaches humanos, clasificaci\u00f3n de los alimentos. Es coherente, y para algunos perfiles es exactamente lo que hace falta. Pero un acompa\u00f1amiento conductual apoyado en un objetivo cal\u00f3rico falso sigue siendo un acompa\u00f1amiento hacia la diana equivocada. Lean trabaja la otra mitad del problema: hacer que esa cifra sea correcta, midiendo cada componente del TDEE (BMR&nbsp;+&nbsp;NEAT&nbsp;+&nbsp;EAT&nbsp;+&nbsp;TEF) m\u00e1s la adaptaci\u00f3n metab\u00f3lica. As\u00ed es como.<\/p>\n\n  <div class=\"method\">\n    <div class=\"m-phone\">\n      <div class=\"duo-row\">\n        <div>\n          <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-bodyscan-result.webp\" alt=\"R\u00e9sultat BodyScan IA : pourcentage de masse grasse mesur\u00e9 par photo\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\">Etapa 1<strong>BodyScan IA<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp\" alt=\"\u00c9cran BMR Lean : m\u00e9tabolisme de base calcul\u00e9 sur la masse maigre\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\">Etapa 2<strong>BMR recalculado<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n    <div>\n      <div class=\"m-tag\">El BMR sobre grasa corporal real<\/div>\n      <h3>Modelo propietario patentado, basado en la masa magra<\/h3>\n      <p>El coaching de Noom parte de un objetivo cal\u00f3rico calculado sobre tu peso. Lean parte de tu <strong>masa magra<\/strong>, porque es ella la que consume en reposo: a igual peso, dos personas no tienen el mismo metabolismo. Falta conocer tu porcentaje de grasa sin pasar por un DEXA en cl\u00ednica.<\/p>\n      <p>De ah\u00ed el <strong>BodyScan IA<\/strong>&nbsp;: una foto, analizada por un modelo entrenado con un banco de esc\u00e1neres DEXA, y tu grasa corporal aparece en unos segundos. Repetido cada semana, actualiza tu metabolismo autom\u00e1ticamente. Ning\u00fan coach humano puede producir esa medici\u00f3n con esa frecuencia.<\/p>\n      <p>Fuera el plic\u00f3metro, la b\u00e1scula de impedancia y sus desviaciones seg\u00fan la hidrataci\u00f3n, el DEXA y su precio. Una foto por semana basta.<\/p>\n    <\/div>\n  <\/div>\n\n  <div class=\"method flip\">\n    <div>\n      <div class=\"m-tag\">Sin coeficiente de actividad<\/div>\n      <h3>NEAT, EAT, TEF calculados por separado<\/h3>\n      <p><strong>NEAT.<\/strong> Tus pasos reales llegan mediante HealthKit (iOS) o Google Fit (Android). Donde un programa de coaching te pide describir tu nivel de actividad, Lean lee los aceler\u00f3metros de tu tel\u00e9fono y convierte esos pasos en calor\u00edas seg\u00fan tu metabolismo. La diferencia entre un d\u00eda de 4&nbsp;000 pasos y uno de 14&nbsp;000 se ve inmediatamente en tu objetivo del d\u00eda.<\/p>\n      <p><strong>EAT.<\/strong> Eliges tu deporte y Lean aplica el MET correspondiente a tu tiempo de esfuerzo real. Una hora de musculaci\u00f3n con sus tiempos de descanso no cuesta lo que una hora de carrera continua: contarlas igual falsea el balance en varios cientos de kcal por semana.<\/p>\n      <p><strong>TEF.<\/strong> La digesti\u00f3n consume energ\u00eda, y no a la misma tarifa seg\u00fan los macros: del 20 al 30&nbsp;% para las prote\u00ednas, del 5 al 10&nbsp;% para los carbohidratos, del 1 al 3&nbsp;% para las grasas. Lean calcula esta partida sobre lo que realmente has comido, en lugar de la tarifa fija del 10&nbsp;% aplicada en todas partes.<\/p>\n    <\/div>\n    <div class=\"m-phone\">\n      <div class=\"mini-row\" style=\"margin:0;gap:10px\">\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp\" alt=\"\u00c9cran NEAT Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">NEAT<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp\" alt=\"\u00c9cran EAT Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">EAT<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp\" alt=\"\u00c9cran TEF Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">TEF<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"method\">\n    <div class=\"m-phone\">\n      <div class=\"mini-phone\" style=\"max-width:170px\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" alt=\"\u00c9cran d\u00e9pense totale Lean avec adaptation m\u00e9tabolique\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">M\u00e9todo<strong>Adaptaci\u00f3n auto<\/strong><\/div>\n    <\/div>\n    <div>\n      <div class=\"m-tag\">Adaptaci\u00f3n metab\u00f3lica autom\u00e1tica<\/div>\n      <h3>Una primicia mundial en una app de consumo<\/h3>\n      <p><strong>La adaptaci\u00f3n metab\u00f3lica.<\/strong> Es el punto ciego de todo programa conductual: al cabo de unas semanas de d\u00e9ficit, tu metabolismo se ralentiza, y ninguna motivaci\u00f3n compensa un objetivo cal\u00f3rico que se ha vuelto falso. Lean ajusta tu TDEE a la baja seg\u00fan las horquillas publicadas (M\u00fcller 2015, Doucet 2001), semana a semana.<\/p>\n      <p>M\u00e1s all\u00e1 del 10 al 15&nbsp;% de adaptaci\u00f3n, la app puede recomendar una vuelta al mantenimiento para relanzar el metabolismo antes de continuar. Es lo que hace un preparador, salvo que Lean lo calcula sobre tus datos.<\/p>\n      <p>Ning\u00fan nivel de actividad que declarar, ninguna casilla marcada de una vez por todas. Cada ladrillo se mide, cada semana.<\/p>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"tab\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">05 &middot; Tabla comparativa<\/span><\/div>\n  <h2 id=\"tab\">Lean frente a Noom, criterio por criterio<\/h2>\n  <p>Lectura honesta de las fortalezas y debilidades de cada app. Ning\u00fan criterio se refiere al precio.<\/p>\n\n  <div class=\"table\" role=\"table\" aria-label=\"Comparativa Lean frente a Noom\">\n    <div class=\"table-row head\" role=\"row\">\n      <div role=\"columnheader\">Criterio<\/div>\n      <div class=\"brand-cell lean\" role=\"columnheader\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> <span>Lean<\/span><\/div>\n      <div class=\"brand-cell\" role=\"columnheader\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/logo-noom-real.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> <span>Noom<\/span><\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">F\u00f3rmula BMR<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Modelo propietario patentado (masa magra)<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Mifflin-St Jeor 1990, sin opci\u00f3n de masa magra<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Tiene en cuenta la grasa corporal<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> S\u00ed, medido en la app<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No, ninguna introducci\u00f3n de grasa corporal posible<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Medici\u00f3n de la grasa corporal en la app<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> BodyScan IA mediante foto<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">NEAT (pasos, actividad fuera del deporte)<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Calculado sobre los pasos reales cada d\u00eda<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Sincronizaci\u00f3n HealthKit, complemento cal\u00f3rico de ejercicio, pero sin rec\u00e1lculo del TDEE<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">EAT (gasto del ejercicio)<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Por deporte mediante MET, tiempo efectivo<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Selecci\u00f3n de deporte simple, base de ejercicios est\u00e1ndar<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">TEF (digesti\u00f3n)<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Calculado seg\u00fan macros, integrado en el TDEE<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No, macros mostrados sin c\u00e1lculo del TEF<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Adaptaci\u00f3n metab\u00f3lica<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Autom\u00e1tica, semana a semana<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Coeficiente de actividad a elegir<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> No, calculado sobre datos reales<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> S\u00ed, nivel est\u00e1tico elegido mediante el cuestionario de registro<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Escaneo fotogr\u00e1fico con IA de un plato<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> S\u00ed, ilimitado<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No, introducci\u00f3n manual o c\u00f3digo de barras<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Escaneo de c\u00f3digo de barras<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> S\u00ed<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> S\u00ed<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Base de datos de alimentos<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> USDA + OpenFoodFacts, curada<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Base propietaria + clasificaci\u00f3n verde\/amarillo\/rojo<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Recomendaci\u00f3n de d\u00e9ficit cal\u00f3rico<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Adaptada al TDEE real<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Objetivo fijo, rec\u00e1lculo manual necesario<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Coaching humano y terapia conductual<\/div>\n      <div class=\"cell lean\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Fuera de alcance, foco en el c\u00e1lculo del TDEE<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Coaches humanos, grupos, cursos diarios<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Clasificaci\u00f3n de alimentos verde\/amarillo\/rojo<\/div>\n      <div class=\"cell lean\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Fuera de alcance<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Referencia pedag\u00f3gica de gran p\u00fablico<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Cobertura EU y localizaci\u00f3n<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> FR, EN, ES, PT, IT, DE, PL, HU<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> EN, ES, DE y otros, fundada en NYC en 2008<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Reputaci\u00f3n y tama\u00f1o de audiencia<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> 4,7\/5, m\u00e1s de 10&nbsp;000 usuarios, app joven<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> 4,5\/5, m\u00e1s de 50M de descargas, audiencia de mujeres de 35 a 55<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Modelo de negocio<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Premium, prueba gratuita de 7 d\u00edas en el plan anual<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Suscripci\u00f3n de pago, periodo de prueba corto<\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"tracking\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">06 &middot; Tracking<\/span><\/div>\n  <h2 id=\"tracking\">3 m\u00e9todos para registrar una comida<\/h2>\n  <p>Un programa de coaching se mantiene en el tiempo si el gesto diario es simple. Es exactamente la apuesta de Lean en el tracking: tres formas de registrar una comida, para que ninguna situaci\u00f3n se convierta en una excusa para abandonar.<\/p>\n\n  <div class=\"mini-row\">\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-database.webp\" alt=\"Recherche dans la base de donn\u00e9es USDA + OpenFoodFacts\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">M\u00e9todo 1<strong>Base de datos<\/strong><\/div>\n    <\/div>\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-codebarre.webp\" alt=\"Scan de code-barres dans Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">M\u00e9todo 2<strong>C\u00f3digo de barras<\/strong><\/div>\n    <\/div>\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-scania.webp\" alt=\"Scan photo IA d'un plat\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">M\u00e9todo 3<strong>Escaneo fotogr\u00e1fico con IA<\/strong><\/div>\n    <\/div>\n  <\/div>\n\n  <ol>\n    <li><strong>B\u00fasqueda en la base de datos.<\/strong> Base curada, USDA + OpenFoodFacts. Sin ruido comunitario, sin \u00ab&nbsp;Pollo asado&nbsp;\u00bb introducido 47 veces por 47 usuarios distintos con 47 valores distintos.<\/li>\n    <li><strong>Escaneo de c\u00f3digo de barras.<\/strong> Est\u00e1ndar. Escaneas tu paquete de pasta, obtienes los macros.<\/li>\n    <li><strong>Escaneo fotogr\u00e1fico con IA de un plato.<\/strong> Fotograf\u00edas tu plato, la IA detecta los alimentos, obtienes las calor\u00edas y los macros por alimento. Noom no ofrece esta funcionalidad.<\/li>\n  <\/ol>\n  <p>El escaneo fotogr\u00e1fico con IA sirve sobre todo cuando comes fuera. Noom te pedir\u00e1 calificar tu plato por color; Lean te pide una foto, y pasas a otra cosa. En un almuerzo de negocios o una cena en casa de amigos, la diferencia de fricci\u00f3n es decisiva.<\/p>\n  <p>Por encima de la comida, Lean muestra un TDEE que se mueve durante el d\u00eda: cuanto m\u00e1s caminas, m\u00e1s sube tu objetivo cal\u00f3rico. Un programa semanal fijo no puede restituir esa variaci\u00f3n diaria.<\/p>\n  <p>Y para jerarquizar lo que realmente cuenta, la Pir\u00e1mide de Progresi\u00f3n:<\/p>\n\n  <div class=\"pyramid\" aria-label=\"Pir\u00e1mide de Progresi\u00f3n Lean\">\n    <div class=\"level l1\"><span>Adherencia<\/span><span class=\"k\">Base<\/span><\/div>\n    <div class=\"level l2\"><span>Objetivo cal\u00f3rico<\/span><span class=\"k\">Nivel 2<\/span><\/div>\n    <div class=\"level l3\"><span>Pasos \/ NEAT<\/span><span class=\"k\">Nivel 3<\/span><\/div>\n    <div class=\"level l4\"><span>Macronutrientes<\/span><span class=\"k\">Cima<\/span><\/div>\n  <\/div>\n  <div class=\"pyramid-cap\">No quemar etapas. Si no eres regular en el tracking, optimizar los macros al uno por ciento no sirve de nada.<\/div>\n<\/section>\n\n<section aria-labelledby=\"noom-better\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">07 &middot; Honestidad<\/span><\/div>\n  <h2 id=\"noom-better\">Lo que Noom hace mejor<\/h2>\n  <p>Lean no es perfecto, y Noom tiene varias fortalezas reales que hay que reconocer. Lectura honesta, criterio por criterio, en los ejes donde Noom sigue por delante. Ninguno de estos ejes es secundario: son pilares reales de la promesa de Noom, y lo que explica su adopci\u00f3n masiva en el p\u00fablico objetivo de mujeres de 35 a 55 a\u00f1os en el tema de la p\u00e9rdida de peso a largo plazo.<\/p>\n\n  <div class=\"scorecard rev\" aria-label=\"Scorecard Noom frente a Lean en 4 ejes psicolog\u00eda y adherencia\">\n    <div class=\"scorecard-head\">\n      <div class=\"h-crit\">Eje<\/div>\n      <div class=\"h-brand\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/logo-noom-real.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> Noom<\/div>\n      <div class=\"h-brand\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> Lean<\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Coaching humano y terapia conductual<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:94%\"><\/i><\/div><div class=\"v\">9,4<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:20%\"><\/i><\/div><div class=\"v\">2,0<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Cursos diarios de psicolog\u00eda alimentaria<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:92%\"><\/i><\/div><div class=\"v\">9,2<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:25%\"><\/i><\/div><div class=\"v\">2,5<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Clasificaci\u00f3n verde\/amarillo\/rojo intuitiva<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:88%\"><\/i><\/div><div class=\"v\">8,8<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:30%\"><\/i><\/div><div class=\"v\">3,0<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Trabajo sobre la adherencia a largo plazo<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:90%\"><\/i><\/div><div class=\"v\">9,0<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:70%\"><\/i><\/div><div class=\"v\">7,0<\/div><\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>Lectura honesta.<\/strong> En coaching humano, Noom es la referencia de gran p\u00fablico: tu coach habla contigo por chat, los grupos de apoyo (comunidad Noom) funcionan de forma continua, y es un verdadero acompa\u00f1amiento emocional para quien lo necesita. En cursos diarios de psicolog\u00eda alimentaria (5 a 10 minutos cada d\u00eda, inspirados en la TCC, terapia cognitivo-conductual), Noom ha invertido masivamente y es \u00fanico en el mercado: ning\u00fan otro tracker de calor\u00edas ofrece este contenido pedag\u00f3gico estructurado. En la clasificaci\u00f3n verde\/amarillo\/rojo, es un mecanismo intuitivo que ahorra tiempo a la usuaria y funciona bien para los perfiles que no quieren sumergirse en los macros. En adherencia a largo plazo, Chin 2016 y numerosos metaan\u00e1lisis sobre la terapia conductual aplicada a la p\u00e9rdida de peso muestran ganancias significativas a 6 y 12 meses. Noom capitaliza cient\u00edficamente este eje.<\/p>\n  <p>Si tu enfoque principal es el trabajo psicol\u00f3gico sobre los h\u00e1bitos alimentarios, si necesitas un coach humano para aguantar, o si la clasificaci\u00f3n verde\/amarillo\/rojo te ayuda a elegir sin calcular, Noom es m\u00e1s relevante que Lean. Si tu enfoque es la precisi\u00f3n del <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/tdee-calculator\/\">c\u00e1lculo del TDEE<\/a>, la grasa corporal medida cada semana mediante BodyScan IA, y la adaptaci\u00f3n metab\u00f3lica autom\u00e1tica, es exactamente lo que acaba de demostrarse en las 3 secciones anteriores. Muchos usuarios usan Lean para la medici\u00f3n y Noom en paralelo para el coaching psicol\u00f3gico, es totalmente defendible.<\/p>\n<\/section>\n\n<section aria-labelledby=\"forwho\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">08 &middot; Para qui\u00e9n<\/span><\/div>\n  <h2 id=\"forwho\">Para qui\u00e9n est\u00e1 hecho Lean<\/h2>\n  <p>Cuatro perfiles. Si uno de ellos te corresponde, Lean tiene posibilidades de convenirte.<\/p>\n\n  <div class=\"persona\">\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Has seguido Noom en serio y no has perdido<\/h4>\n        <p>Hiciste el cuestionario, seguiste los cursos, clasificaste tus comidas por color, hablaste con tu coach, y aguantaste varias semanas sin que la curva siguiera de verdad.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Te estancas tras varias semanas de definici\u00f3n<\/h4>\n        <p>La meseta se instala tras cuatro a ocho semanas. Es la firma de la adaptaci\u00f3n metab\u00f3lica: Lean la calcula y corrige tu objetivo en lugar de remitirte a tu motivaci\u00f3n.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Quieres entender tu metabolismo<\/h4>\n        <p>Quieres ver el detalle del c\u00e1lculo: BMR, NEAT, EAT y TEF mostrados por separado, adaptaci\u00f3n explicada aparte, en lugar de una cifra \u00fanica comentada por un coach.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Quieres un tracking que dure 12 meses<\/h4>\n        <p>Comes a menudo fuera y necesitas un registro r\u00e1pido: foto, base curada o c\u00f3digo de barras seg\u00fan el contexto.<\/p>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>Noom sigue siendo m\u00e1s relevante para<\/strong>&nbsp;: trabajar psicol\u00f3gicamente los h\u00e1bitos alimentarios, disfrutar de un coach humano y de grupos de apoyo, seguir cursos diarios de terapia cognitivo-conductual aplicados a la p\u00e9rdida de peso, o apoyarse en la clasificaci\u00f3n verde\/amarillo\/rojo para elegir sin calcular. La precisi\u00f3n del c\u00e1lculo del TDEE y la adaptaci\u00f3n metab\u00f3lica simplemente no forman parte de su promesa principal.<\/p>\n<\/section>\n\n<section aria-labelledby=\"migrate\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">09 &middot; Migraci\u00f3n<\/span><\/div>\n  <h2 id=\"migrate\">Pasar de Noom a Lean (o usar los dos) en 3 minutos<\/h2>\n\n  <div class=\"steps\">\n    <div class=\"step\"><div class=\"sn\">01<\/div><h4>Descarga Lean<\/h4><p>App Store o Play Store. Registro en treinta segundos, sin cuestionario de veinte minutos.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">02<\/div><h4>BodyScan IA<\/h4><p>Una foto, cinco segundos: tu porcentaje de grasa aparece.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">03<\/div><h4>Peso &amp; altura<\/h4><p>Introduces tu peso y tu altura. No se pide nada m\u00e1s.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">04<\/div><h4>Lean calcula<\/h4><p>BMR sobre masa magra real, NEAT a partir de tus pasos mediante HealthKit o Google Fit, EAT por MET, TEF sobre tus macros, y la adaptaci\u00f3n metab\u00f3lica que lo modula todo semana a semana.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">05<\/div><h4>Registra una comida<\/h4><p>Foto, c\u00f3digo de barras o base de datos: eliges seg\u00fan la comida.<\/p><\/div>\n  <\/div>\n\n  <p style=\"margin-top:24px\"><strong>Nota importante.<\/strong> Lean no importa tu historial de Noom autom\u00e1ticamente, ni tus conversaciones con tu coach humano. Si aprecias el coaching psicol\u00f3gico de Noom y los cursos diarios, muchos usuarios siguen usando Noom para el trabajo conductual y los grupos de apoyo, usando Lean a diario para el c\u00e1lculo del TDEE y el tracking preciso. La sincronizaci\u00f3n HealthKit \/ Google Health Connect, en cambio, toma el relevo inmediatamente para tus pasos y tu historial de actividad.<\/p>\n\n  <div class=\"cta-band rev\">\n    <div class=\"l\">Descarga Lean y empieza el BodyScan IA ahora mismo. Registro gratuito.<\/div>\n    <div class=\"stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"deblock-h\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">10 &middot; Lo que Lean desbloquea<\/span><\/div>\n  <h2 id=\"deblock-h\">Lo que Lean hace, y que Noom no hace (en el TDEE)<\/h2>\n  <p>Seis funcionalidades ausentes de los trackers de consumo. Todas se basan en la misma elecci\u00f3n: medir cada componente del TDEE en lugar de estimarlo, y luego vestirlo de pedagog\u00eda.<\/p>\n\n  <div class=\"feat-stack\">\n    <div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">BodyScan IA ilimitado<\/div><p class=\"fd\">Tu porcentaje de grasa, obtenido a partir de una foto y actualizado cada semana. Es la variable que hace el metabolismo individual, y ning\u00fan programa de coaching la mide.<\/p><\/div><div class=\"fc\">Grasa corporal<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">Escaneo fotogr\u00e1fico con IA de un plato ilimitado<\/div><p class=\"fd\">Una comida en el restaurante registrada en dos segundos, sin b\u00e1scula ni introducci\u00f3n manual. La fricci\u00f3n de menos que permite aguantar doce meses, sin necesidad de que un coach te insista.<\/p><\/div><div class=\"fc\">Adherencia<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">Adaptaci\u00f3n metab\u00f3lica autom\u00e1tica<\/div><p class=\"fd\">Tu TDEE se corrige semana a semana seg\u00fan las horquillas publicadas. Las mesetas que un acompa\u00f1amiento atribuye a la motivaci\u00f3n encuentran aqu\u00ed su explicaci\u00f3n en cifras.<\/p><\/div><div class=\"fc\">Adaptaci\u00f3n<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">04<\/div><div><div class=\"ft\">TDEE desglosado en vivo<\/div><p class=\"fd\">BMR, NEAT, EAT y TEF mostrados por separado y actualizados durante el d\u00eda. Tu objetivo se mueve con tu actividad real, en lugar de quedar fijado al despertar.<\/p><\/div><div class=\"fc\">En vivo<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">05<\/div><div><div class=\"ft\">Historial completo y tendencias<\/div><p class=\"fd\">Tus tendencias de peso, grasa corporal y masa magra durante varios meses. Identificas tus ciclos en lugar de reaccionar al pesaje del d\u00eda.<\/p><\/div><div class=\"fc\">Historial<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">06<\/div><div><div class=\"ft\">3 m\u00e9todos de tracking unificados<\/div><p class=\"fd\">Una jerarqu\u00eda clara de lo que cuenta: la adherencia primero, luego el objetivo cal\u00f3rico, luego los pasos. Para saber qu\u00e9 ajustar cuando se bloquea.<\/p><\/div><div class=\"fc\">Tracking<\/div><\/div>\n  <\/div>\n\n  <p style=\"margin-top:26px\">Instalas la app gratis, pruebas sin compromiso y luego decides si la herramienta encaja con tu objetivo.<\/p>\n<\/section>\n\n<section aria-labelledby=\"faq-h\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">11 &middot; FAQ<\/span><\/div>\n  <h2 id=\"faq-h\">Preguntas frecuentes<\/h2>\n  <div class=\"faq\">\n    <details><summary>Noom es conocido por su coaching psicol\u00f3gico, \u00bfpor qu\u00e9 compararlo con Lean en el TDEE?<\/summary><div class=\"ans\">Noom es reconocido por su enfoque conductual (cursos diarios inspirados en la TCC, coaches humanos, clasificaci\u00f3n de alimentos verde\/amarillo\/rojo). Es una fuerza real para la adherencia y el trabajo psicol\u00f3gico sobre la alimentaci\u00f3n. Pero el motor cal\u00f3rico subyacente sigue siendo Mifflin-St Jeor 1990 sin grasa corporal, m\u00e1s un factor de actividad est\u00e1tico elegido mediante el cuestionario de registro. En el TDEE, el motor es b\u00e1sico. Lean recalcula cada d\u00eda tu BMR sobre tu grasa corporal real medida por BodyScan IA, y lo modula con la adaptaci\u00f3n metab\u00f3lica. Las dos apps no juegan en el mismo terreno.<\/div><\/details>\n    <details><summary>\u00bfPor qu\u00e9 Noom no calcula el BMR sobre la grasa corporal real?<\/summary><div class=\"ans\">Noom aplica Mifflin-St Jeor 1990 por defecto sin opci\u00f3n de masa magra. Ninguna medici\u00f3n de grasa corporal est\u00e1 integrada en la app, y ninguna ecuaci\u00f3n tipo Katch-McArdle se ofrece ni siquiera en los ajustes avanzados. La consecuencia es mec\u00e1nica: dos usuarias del mismo peso pero con un 22 y un 38 por ciento de grasa corporal obtienen el mismo BMR Noom, cuando su gasto real puede diferir en 400 kcal al d\u00eda. Lean integra el BodyScan IA para medir tu grasa corporal a partir de una simple foto, a repetir cada semana.<\/div><\/details>\n    <details><summary>\u00bfLa clasificaci\u00f3n verde\/amarillo\/rojo de Noom es una verdadera medida metab\u00f3lica?<\/summary><div class=\"ans\">No. El sistema verde\/amarillo\/rojo clasifica los alimentos por densidad cal\u00f3rica (verduras en verde, f\u00e9culas en amarillo, grasas y az\u00facares en rojo). Es una herramienta pedag\u00f3gica de comportamiento alimentario, no una medida de gasto energ\u00e9tico. Es eficaz para tomar conciencia de las elecciones, pero no influye en el c\u00e1lculo del TDEE. En tu metabolismo real, Noom sigue en Mifflin 1990 m\u00e1s unas casillas de actividad est\u00e1tica. La clasificaci\u00f3n por colores no modifica el objetivo cal\u00f3rico calculado.<\/div><\/details>\n    <details><summary>Noom importa los pasos mediante HealthKit, \u00bfbasta para el NEAT?<\/summary><div class=\"ans\">Noom importa los pasos y la actividad mediante Apple Health y Google Fit, pero los usa para estimar un gasto de ejercicio a\u00f1adido al objetivo cal\u00f3rico diario. El factor de actividad est\u00e1tico elegido en el cuestionario de registro sigue siendo la base del c\u00e1lculo del TDEE. Lean, al contrario, calcula el NEAT directamente a partir de los pasos reales medidos cada d\u00eda, sin coeficiente que elegir.<\/div><\/details>\n    <details><summary>\u00bfEl coaching humano de Noom sustituye un c\u00e1lculo preciso del TDEE?<\/summary><div class=\"ans\">El coaching humano de Noom es un verdadero valor a\u00f1adido para la adherencia y el trabajo psicol\u00f3gico sobre los h\u00e1bitos. Chin 2016 y numerosos metaan\u00e1lisis muestran que la terapia conductual mejora la p\u00e9rdida de peso a 6 y 12 meses. Pero el coaching no act\u00faa sobre la ecuaci\u00f3n del TDEE subyacente. Si tu objetivo cal\u00f3rico est\u00e1 calculado con Mifflin 1990 sin grasa corporal y un PAL est\u00e1tico, tu coach no va a corregir la ecuaci\u00f3n, va a animarte a mantener un d\u00e9ficit potencialmente falso. El coaching es un multiplicador de adherencia, no un sustituto de la medici\u00f3n objetiva.<\/div><\/details>\n    <details><summary>\u00bfSe pueden usar Lean y Noom en paralelo?<\/summary><div class=\"ans\">S\u00ed, es defendible. Si aprecias el coaching humano de Noom, los cursos diarios y la pedagog\u00eda conductual, puedes conservar Noom para el aspecto psicol\u00f3gico y de h\u00e1bitos. Lean se encarga del motor metab\u00f3lico preciso (BMR sobre grasa corporal real, NEAT, EAT, TEF, adaptaci\u00f3n). Las bases de datos son diferentes (USDA + OpenFoodFacts en Lean, base propietaria en Noom), as\u00ed que el esfuerzo de doble registro es real: es un trade-off a decidir seg\u00fan tus prioridades.<\/div><\/details>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"conclu\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">12 &middot; Conclusi\u00f3n<\/span><\/div>\n  <h2 id=\"conclu\">Coaching frente a medici\u00f3n<\/h2>\n  <p>No es Noom frente a Lean en marketing. Es el coaching psicol\u00f3gico frente a la precisi\u00f3n metab\u00f3lica, dos promesas diferentes.<\/p>\n  <p>Noom sigue siendo una de las mejores apps de consumo para el trabajo conductual sobre la alimentaci\u00f3n, y nadie en el gran p\u00fablico lo hace mejor en cursos diarios de psicolog\u00eda alimentaria y acompa\u00f1amiento por coach humano. Pero para tu TDEE, Noom usa Mifflin-St Jeor 1990 sin grasa corporal medida en la app, m\u00e1s un factor de actividad fijo que marcas una sola vez durante el cuestionario de registro, e ignora la adaptaci\u00f3n metab\u00f3lica. La combinaci\u00f3n de los tres hace imposible cualquier seguimiento cal\u00f3rico preciso m\u00e1s all\u00e1 de unas semanas de definici\u00f3n. Es matem\u00e1tico. Ning\u00fan coach humano corrige una ecuaci\u00f3n que no ve.<\/p>\n  <p>Lean se construy\u00f3 para hacer exactamente lo contrario: BMR basado en la <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/depense-energetique-totale-v2\/\">grasa corporal real<\/a> (medido por BodyScan IA) mediante un modelo propietario patentado, <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/neat-depense-non-sportive\/\">NEAT por pasos reales<\/a>, EAT por deporte y MET, <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/effet-thermique-des-aliments\/\">TEF por macros<\/a>, m\u00e1s la adaptaci\u00f3n metab\u00f3lica que modula el BMR semana a semana. Cada componente calculado con precisi\u00f3n, sin coeficiente m\u00e1gico, sin envoltorio psicol\u00f3gico.<\/p>\n  <p>Noom sigue siendo muy s\u00f3lido en coaching conductual y acompa\u00f1amiento humano. Los mejores resultados suelen venir de combinar los dos: medir bien (Lean) Y actuar con disciplina (a veces con la ayuda de un coach de Noom). Si has probado Noom en serio y no has tenido los resultados que esperabas en tu definici\u00f3n, el problema no eres t\u00fa, ni Noom en su promesa psicol\u00f3gica. El problema es el TDEE congelado bajo el cap\u00f3. Cambia el motor, conserva el coach en paralelo si lo necesitas.<\/p>\n<\/section>\n\n<div class=\"get-band rev\">\n  <div class=\"kicker\">Descarga<\/div>\n  <h3>Lean se puede descargar gratis<\/h3>\n  <p>iOS y Android. El BodyScan IA funciona con una simple foto. Sin plic\u00f3metro, sin b\u00e1scula de impedancia, sin DEXA.<\/p>\n  <div class=\"stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\" aria-label=\"Descargar Lean en la App Store\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\" aria-label=\"Descargar Lean en Google Play\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n  <\/div>\n<\/div>\n\n<section aria-labelledby=\"links\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">Para ir m\u00e1s lejos<\/span><\/div>\n  <h3 id=\"links\" style=\"margin-top:0\">Enlaces internos<\/h3>\n  <ul>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/tdee-calculator\/\">Calculadora TDEE gratuita en l\u00ednea<\/a> &middot; versi\u00f3n web, sin registro, misma l\u00f3gica que la app (BMR + NEAT + EAT + TEF).<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/depense-energetique-totale-v2\/\">Entender el TDEE en detalle (BMR, NEAT, EAT, TEF, adaptaci\u00f3n)<\/a> &middot; art\u00edculo cient\u00edfico de fondo.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/comment-compter-ses-calories\/\">C\u00f3mo contar tus calor\u00edas correctamente<\/a> &middot; gu\u00eda pr\u00e1ctica para principiantes.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/neat-depense-non-sportive\/\">NEAT&nbsp;: gasto por pasos y actividad fuera del deporte<\/a>.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/effet-thermique-des-aliments\/\">TEF&nbsp;: la digesti\u00f3n quema calor\u00edas<\/a>.<\/li>\n  <\/ul>\n<\/section>\n\n<section aria-labelledby=\"src\" class=\"sources\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">Fuentes<\/span><\/div>\n  <h3 id=\"src\" style=\"margin-top:0;color:var(--ink)\">Bibliograf\u00eda<\/h3>\n  <ol>\n    <li>Harris J.A., Benedict F.G. (1919). A Biometric Study of Basal Metabolism in Man. Carnegie Institution of Washington.<\/li>\n    <li>Mifflin M.D. et al. (1990). A new predictive equation for resting energy expenditure in healthy individuals. American Journal of Clinical Nutrition.<\/li>\n    <li>Katch V.L., McArdle W.D. (1973). Prediction of body density from simple anthropometric measurements in college-age men and women. Human Biology.<\/li>\n    <li>Chin S.O. et al. (2016). Successful weight reduction and maintenance by using a smartphone application in those with overweight and obesity. Scientific Reports, behavioral therapy and weight loss.<\/li>\n    <li>Frankenfield D.C. et al. (2013). Validation of Mifflin-St Jeor equation in obese and non-obese populations. PubMed 23631843.<\/li>\n    <li>M\u00fcller M.J., Bosy-Westphal A. (2015). Adaptive thermogenesis with weight loss in humans. Obesity, revisi\u00f3n de Minnesota. PubMed 26399868.<\/li>\n    <li>Doucet E. et al. (2001). Evidence for the existence of adaptive thermogenesis during weight loss. British Journal of Nutrition.<\/li>\n    <li>Westerterp K.R. (2004). Diet induced thermogenesis. Nutrition and Metabolism.<\/li>\n  <\/ol>\n<\/section>\n\n<\/main>\n\n<footer>\n  <div class=\"wrap\">\n    <div class=\"row\">\n      <div>\n        <div class=\"kicker\">Lean &middot; lean-app.com<\/div>\n        <p>Art\u00edculo publicado el 24 de mayo de 2026. Actualizado regularmente con las opiniones de los usuarios y los nuevos estudios relevantes. 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-->\n<aside class=\"lean-mesh\" style=\"margin:48px auto;max-width:760px;padding:24px 28px;background:#ffffff;border-left:4px solid #FF2D6E;border-radius:0 12px 12px 0;box-shadow:0 6px 24px rgba(20,20,40,0.06);font-family:-apple-system,'SF Pro Text','Segoe UI',Roboto,Arial,sans-serif;color:#1a1a2e;\"><p style=\"margin:0 0 14px;font-size:13px;font-weight:700;letter-spacing:0.06em;text-transform:uppercase;color:#FF2D6E;\">Lecturas relacionadas<\/p><ul style=\"list-style:none;padding:0;margin:0;display:grid;grid-template-columns:1fr;gap:10px;\"><li><a href=\"https:\/\/lean-app.com\/es\/metabolisme-de-base\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Metabolismo basal (BMR): todo lo que hay que saber para calcularlo <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Definici\u00f3n, ecuaci\u00f3n TDEE, 4 f\u00f3rmulas hist\u00f3ricas, por qu\u00e9 la grasa corporal lo cambia todo.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/depense-energetique-totale-v2\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Gasto energ\u00e9tico total (TDEE): la f\u00f3rmula can\u00f3nica BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Entiende los 4 bloques + la adaptaci\u00f3n metab\u00f3lica, fuentes cient\u00edficas 2025.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/comparatifs-croises\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">\u00bfMyFitnessPal o Yazio? 12 duelos de apps de calor\u00edas comparados <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">El veredicto de cada duelo de un vistazo: qui\u00e9n gana en qu\u00e9, y lo que ninguna de las dos calcula.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/meilleures-applications-calories-2026\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Mejores aplicaciones para contar calor\u00edas en 2026: 8 apps probadas <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Lean, MFP, Cronometer, Yazio, Lifesum, FatSecret, Noom, Foodvisor.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/alternative-myfitnesspal\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">\u00bfQu\u00e9 alternativa a MyFitnessPal en 2026? 5 apps probadas <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Comparativa honesta, precisi\u00f3n del TDEE, ergonom\u00eda.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/comparatifs\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Todas las comparativas de Lean frente a las grandes apps de calor\u00edas <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Hub: MyFitnessPal, Yazio, Cronometer, Lifesum, FatSecret, Noom.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/lean-vs-myfitnesspal\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean frente a MyFitnessPal: la f\u00f3rmula TDEE que lo cambia todo <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Por qu\u00e9 MFP se equivoca en tu gasto cal\u00f3rico real.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/lean-vs-foodvisor\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean frente a Foodvisor: pionero del escaneo de fotos vs gasto real <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Foodvisor ve tu plato. Lean recompone tu TDEE de forma continua.<\/span><\/a><\/li><\/ul><\/aside>","protected":false},"excerpt":{"rendered":"<p>Lean Calculateur TDEE Accueil &nbsp;\/&nbsp; Lean vs Noom Comparatif &middot; Nutrition &amp; TDEE Lean face \u00e0 Noom. Coaching psychologique face \u00e0 la pr\u00e9cision m\u00e9tabolique. Noom vend du coaching comportemental pour changer tes habitudes. Lean voit ta d\u00e9pense r\u00e9elle. Deux promesses qui ne jouent pas sur le m\u00eame terrain. L&rsquo;\u00e9quipe Lean &middot; Lecture 12&nbsp;min &middot; Mis [&hellip;]<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-lvm-blank","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1425","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Lean vs Noom: \u00bfcoaching o precisi\u00f3n metab\u00f3lica? - Lean<\/title>\n<meta name=\"description\" content=\"Noom apuesta por el coaching conductual, Lean por el c\u00e1lculo exacto de tu gasto. 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